Signal Processing for Data Analysis

I was a teaching assistant for DSC 120 offered by Prof. Alex and Prof. Gal. I held discussion sessions and office hours; prepared and evaluated exams in the course. The course focuses on ideas from both classical and modern signal processing, with the main themes of sampling continuous data and building informative representations of data using orthonormal bases, frames, and data dependent operators. The main topics are sampling theory, Fourier analysis, lossy transformations and compression, time and spatial filters, and random Fourier features and their connections to kernel methods. The main sources of data that are used are time series and streaming signals, and various imaging modalities.